Performance Analysis of Active Shape Reconstruction of Fractured, Incomplete Skulls

  • Kun Zhang
  • Wee  Kheng LeowEmail author
  • Yuan Cheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9256)


Reconstruction of normal skulls from deformed skulls is a very important but difficult task in practice. Active shape model (ASM) is among the most popular methods for reconstructing skulls. To apply ASM to skull reconstruction, it is necessary to establish shape correspondence among the training and testing samples because wrong correspondence will introduce unwanted shape variations in ASM reconstruction. Despite the popularity of ASM, the accuracy of ASM skull reconstruction has not been well investigated in existing literature. In particular, it is unclear how to estimate the reconstruction error of skulls without ground truth. This paper aims to investigate the source of error of ASM skull reconstruction. Comprehensive tests show that the error of accurate correspondence algorithm is uncorrelated and small compared to reconstruction error. On the other hand, ASM fitting error is highly correlated to reconstruction error, which allows us to estimate the reconstruction error of real deformed skulls using ASM fitting error. Moreover, ASM fitting error is correlated to the severity of skull defects, which places a limit on the reconstruction accuracy that can be achieved by ASM.


Reconstruction Error Soft Constraint Active Shape Model Mesh Vertex Target Mesh 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceNational University of SingaporeSingaporeSingapore

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